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Proceedings Paper

Application of multiple signal classification algorithm to frequency estimation in coherent dual-frequency lidar
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Paper Abstract

Coherent dual-frequency Lidar (CDFL) is a new development of Lidar which dramatically enhances the ability to decrease the influence of atmospheric interference by using dual-frequency laser to measure the range and velocity with high precision. Based on the nature of CDFL signals, we propose to apply the multiple signal classification (MUSIC) algorithm in place of the fast Fourier transform (FFT) to estimate the phase differences in dual-frequency Lidar. In the presence of Gaussian white noise, the simulation results show that the signal peaks are more evident when using MUSIC algorithm instead of FFT in condition of low signal-noise-ratio (SNR), which helps to improve the precision of detection on range and velocity, especially for the long distance measurement systems.

Paper Details

Date Published: 12 January 2018
PDF: 6 pages
Proc. SPIE 10619, 2017 International Conference on Optical Instruments and Technology: Advanced Laser Technology and Applications, 1061909 (12 January 2018); doi: 10.1117/12.2295527
Show Author Affiliations
Ruixiao Li, Beijing Institute of Technology (China)
Kun Li, Beijing Institute of Satellite Information Engineering (China)
Changming Zhao, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 10619:
2017 International Conference on Optical Instruments and Technology: Advanced Laser Technology and Applications
Zhiyi Wei; Chunqing Gao; Pu Wang; Franz X. Kärtner; Jayanta Kumar Sahu; Liquan Dong, Editor(s)

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